PR to add `torch.index_put` operator to TVM PyTorch frontend
https://github.com/apache/tvm/pull/7465
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I faced an issue with scatter_nd and concatenate
https://discuss.tvm.apache.org/t/scatter-nd-and-concatenate-fails/9138
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To uns
`scatter_nd` might work if we assume that `input_put_` usually sets the values
to empty tensor.
```
ctx = tvm.cpu(0)
target = 'llvm'
dtype = 'float32'
shape = (3,3)
tp = relay.TensorType(shape)
data = np.random.rand(*shape).astype(dtype)
hs = [0, 1, 2, 2]
ws = [0, 1, 1, 2]
vs = [2.0, 4.0, 7.0,
Actual torchscript from some model looks the following
torchscript Python:
```
output = torch.zeros([_17, int(num_channels), 7, 7], dtype=6, layout=None,
pin_memory=False)
output0 = torch.index_put_(output, _20, _19, False)
```
torchscript IR:
```
%output.1 : Float(1000, 256, 7, 7, str
Note that Relay is a functional language, so modify tensors in place is
awkward. In this case, the tensor you are modifying has zeros by default, so
you can use `scatter_nd`.
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Probably `scatter_nd`, see https://github.com/apache/tvm/pull/6854
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What operator in Relay can be used to set multiple values to a given tensor?
Lets say I have 3x3 tensor "A" and I need to set
```
A[0,0] = 2.0
A[1,1] = 4.0
A[2,1] = 7.0
A[2,2] = 9.0
```
PyTorch code:
```
A = torch.zeros(3,3)
hs = torch.tensor([0, 1, 2, 2])
ws = torch.tensor([0, 1, 1, 2])
vs =
